how to plot the linear regression in R?

Question

I want to make the following case of linear regression in R

year<-rep(2008:2010,each=4)
quarter<-rep(1:4,3)
cpi<-c(162.2,164.6,166.5,166.0,166.4,167.0,168.6,169.5,170.0,172.0,173.3,174.0)
plot(cpi,xaxt="n",ylab="CPI",xlab="")
axis(1,labels=paste(year,quarter,sep="C"),at=1:12,las=3)
fit<-lm(cpi~year+quarter)

I want to plot the line that shows the linear regression of the data that I process. I have tried with:

abline(fit)
abline(fit$coefficients[[1]],c(fit$coefficients[[2]],fit$coefficients[[3]]))

The problem is that my formula is of the form:

y=a+b*year+c*quarter

and not something simpler like:

y=a+b*year

so how I can draw that line that shows the linear regression?

Is it possible to draw the line with abline?

Answer 1

Are you looking for the predict function?

E.g.: using lines(predict(fit)) will give:

You could also use this for predicting future data aligning with the calculated coefficients. E.g.

# plot the existing data with space for the predicted line
plot(c(cpi,rep(NA,12)),xaxt="n",ylab="CPI",xlab="",ylim=c(162,190))

# plot the future predictions as a line using the next 3 year periods
lines(13:24,
      predict(
        fit,
        newdata=data.frame(year=rep(c(2011,2012,2013),each=4),quarter=rep(1:4,3))
             )
     )

year<-rep(2008:2013,each=4)
axis(1,labels=paste(year,quarter,sep="C"),at=1:24,las=3)

Answer 2

The error lies in the way you're data was formatted. Here is another option:

year<-seq(from=2008,to=2010.75,by=.25)
cpi<-c(162.2,164.6,166.5,166.0,166.4,167.0,168.6,169.5,170.0,172.0,173.3,174.0)
df <- data.frame(year,cpi)
plot(df)+abline(lm(df$cpi~df$year))

Then you can reformat the axes labels if you like.